The Louvain method is a simple, yet powerful heuristic clustering algorithm, proposed by Blondel et al. [1]}. The method is based on an iterative, unsupervised, two-step procedure that optimizes modularity \(m\) .
Initially, a directed graph \(G\)  with an \(N\times N\)  weighted adjacency matrix \(M\)  is partitioned in \(N\)  clusters, where each node constitutes its own cluster or community.
